In recent years, the popularity of systems using wireless radio communication has increased substantially. For example, cellular communication systems and wireless networks have now become commonplace. The increased requirement for frequency spectrum resource has led to an increased desire for efficient communication and especially at higher frequencies and for higher data rates.
For example, Broadband Wireless Access (BWA) systems are becoming common not only in fixed deployments but also in mobile deployments. In order to increase the capacity of such BWA systems, it is desirable to increase the data rate of the wireless communication. As a specific example, the Institute of Electrical and Electronic Engineers (IEEE) have formed a committee for standardizing an advanced air interface for operation in licensed bands known as IEEE 802.16m (Trademark). The 802.16m™ standard comprises BWA Medium Access Control (MAC) and Physical Layer (PHY) specifications aimed at enhancing BWA systems to meet the cellular layer requirements of International Telecommunications Union Radiocommunications Sector (IMT-Advanced) next generation mobile networks. Similarly, Wireless Local Area Networks (WLANs) are becoming common not only in business environments but also in domestic environments. The IEEE has formed a committee for standardizing a very high-speed WLAN standard known as IEEE 802.11vht. It is intended that the 802.11vht™ standard will help WLANs meet the expanding bandwidth needs of enterprise and home networks, as well as those of WLAN hot spots. Other popular examples of wireless networks include the more popular names of WiFi™ and WiMAX™ (corresponding to IEEE 802.11n and IEEE 802.16e).
In order to achieve high data rates over the air interface, a number of advanced radio techniques are employed. It has been found that significant improvement can be achieved by using multiple antennas at the transmitter and the receiver. In particular, many radio communication systems, such as WLANs, provide for a plurality of transmit and receive antennas to be used. Specifically, some transmission techniques involve transmitting a data stream by simultaneously transmitting different signals derived from the data stream from different antennas over the same communication channel. The receiver(s) of these techniques typically also comprise a plurality of antennas each of which receive a combined signal corresponding to the transmitted signals modified by the individual propagation characteristics of the radio link between the individual antennas. The receiver may then retrieve the transmitted data stream by evaluating the received combined signal.
Such techniques may be used in closed loop configurations wherein the receiver communicates information back to the transmitter allowing this to weight the signals to the individual antennas. Specifically, data may be fed back to the transmitter to allow this to implement suitable beamforming or pre-equalization. Such open and closed loop techniques are known as Multiple Transmit Multiple Receive (MTMR) or Multiple Input Multiple Output (MIMO) schemes and can be designed to derive benefit from spatial diversity between the antennas in order to improve detection. Indeed, both the equivalent Signal to Noise Ratio (SNR) of the combined signal and the available degrees of freedom are typically increased compared to the single antenna case thereby allowing higher channel symbol rates or higher order constellations. This may increase the data rate for the communication link and thus the capacity of the communication system.
In MIMO, the transmitted signals from each transmit antenna are typically weighted to provide improved performance. One technique is to apply a weight to each antenna in order to compensate for the experienced channel conditions. This approach is known as pre-equalization and utilizes linear precoding at the transmitter for interference suppression and to allow an increased number of users. However, it tends to suffer from the limitation that it in principle requires unconstrained transmitted energy from the multiple antennas and thus in practice results in high peak transmit powers.
In order to address this limitation, a vector perturbation technique has been introduced. This non-linear technique combines the conventional linear precoding with an extended symbol set. The transmitted energy from the multiple antennas is constrained by selecting the transmitted symbols from an extended symbol set which comprises not only the constellation points of the original constellation but also a large number of replicated constellations of this fundamental constellation. Thus, with vector perturbation, a constellation pattern is generated with translated/offset copies of the constellation points of the basic constellation. A data symbol corresponding to a specific constellation point of the basic constellation may be selected to be represented by a channel symbol corresponds to any replications of the specific constellation point. Thus, the transmitted channel symbols may be selected as the constellation points for which the transmit processing (the weighting and summation for each transmit antenna) results in the smallest overall transmit power.
The receiver may then decode the received symbols by applying a modulo function that results in all replicated constellation points being transformed to the same constellation point. One specific way of selecting the channel symbols from the replicated constellations is known as sphere encoding and is based on a closest lattice point search algorithm that minimizes the Euclidean norm (energy) of the transmitted vector.
Hence, an improved system would be advantageous and in particular a system allowing increased flexibility, reduced error rate, simplified receiver operation, reduced complexity, improved trade-off between transmit power and error performance and/or improved performance would be advantageous.